Optimizing Cargo Heating For Tankers

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1 Optimizing Cargo Heating For Tankers ELINT Annual Meeting Vassilios Dimoulas Hellenic Plan Approval Office Manager

2 Facts A series of crude oil and fuel oil cargoes require heating during the voyage Cargo temperature should not fall below a specific level dependent upon the cargo pour point and cloud point Boiler fuel oil consumption for cargo heating during a tanker voyage is a significant figure (e.g. 100 to 200 tons for an Aframax) Heating systems are designed according to specific design environmental conditions and requirements for cargo heating up rate Significant consumption gains may be realized by applying and following an optimized cargo heating schedule Cargo and bunker management heating is part of the IMO Ship Energy Efficiency Management Plan (SEEMP, MEPC.1/Circ.683 and 684) Detailed Heating Logs are required to be kept by the crew 2

3 Heating practices Extract of IMO/OCIMF example SEEMP: 3

4 The CHS Software tool 4

5 The CHS Software tool Main Features: Automatic calculation of optimum cargo heating schedule Vessel Specific Cargo tanks interact with each other, the adjacent spaces and environment by applying a complete heat transfer model Effects of change of any of the parameters (environment, cargo type, cargo temperature) to the steam and fuel consumption are observed on the fly Follow up of the actual voyage by entering measured temperature values and readjustment of the heating schedule Storing and retrieval of previous voyage plans Visualization of plan by using graphs Printing of full reports 5

6 CHS thermodynamic model Heat loss (conduction): Tair Tcargo (S) Tair Tcargo (P) Tsea Depends on temperature difference, surface area and heat loss coefficient for each surface: HL = h x S x (T 1 -T 2 ) 6

7 CHS thermodynamic model Heating up: t T 2 T 1 Required Heating rate depends on cargo mass, specific heat constant, temperature temperature difference and target time for heating up: HR = mc x SH x (T 2 -T 1 ) / t 7

8 CHS thermodynamic model Total heating energy is the sum of the energy needed to overcome the losses and provide the required cargo heating up Total required steam capacity is calculated using steam enthalpy tables Fuel consumption is calculated using boiler consumption curves 8

9 CHS Representative screens Loading condition 9

10 Voyage Data Entry: Cargo tanks interact with each other and the adjacent spaces Effects of change in parameters are observed on the fly Constant calculation of the total fuel consumption on the top of the page Simulation of boiler shut off by calculation of the daily temperature drop 10

11 Automatic Optimum Schedule Tool: Simply click the Optimize button The software calculates the optimum initial cooling down period in days Linear increase in temperature is applied thereafter to reach the contracted delivery temperature Cargo minimum transit temperature is observed 11

12 Diagrams: Diagrams available for each cargo tank or for all tanks weighted average Optimized schedule is shown in this example 12

13 Actual heating log function for voyage reporting: Locked Days For each day passed actual measured figures are entered. The day can then be locked and optimizing or calculation functions for scheduling applied only to the remaining days of the voyage 13

14 Exporting of heating log form in Excel: Form can be customized to fit company existing forms and practice 14

15 Worked example Suezmax actual 52 day Voyage with 2 cargo grades as reported by Master: Voy No: 62 Cargo Name: 1ST GRADE : BACHAQUERO C.O 1W-4W-6W-SLOP S API: 11.3 Pour Point: 48.2 F Page: 2ND GRADE: BOSCAN C.O 2W -3W-5W-SLOP P API: 10.3 Pour Point: 55.4 F Page: DATE 1 AIR SEA HFO CARGO TANKS (DEG. C) AVG-1 TOTAL AVG-2 F TEMP TEMP CONS 1P 1S 2P 2S 3P 3S 4P 4S 5P 5S 6P 6S SL-P SL-S F AVERAGE 09/06/ KG 10/06/ KG 11/06/ KG 12/06/ KG 13/06/ KG 14/06/ KG 15/06/ KG 16/06/ KG 17/06/ KG 18/06/ KG 19/06/ KG 20/06/ KG 21/06/ KG 22/06/ KG 23/06/ KG 24/06/ KG 25/06/ KG 26/06/ KG 27/06/ KG 28/06/ KG 29/06/ KG 30/06/ KG 01/07/ KG 02/07/ KG 03/07/ KG 04/07/ KG 05/07/ KG 06/07/ KG 07/07/ KG 08/07/ KG 09/07/ KG 10/07/ KG 11/07/ KG 12/07/ KG 13/07/ KG 14/07/ KG 15/07/ KG 16/07/ KG 17/07/ KG 18/07/ KG 19/07/ KG 20/07/ KG 21/07/ KG 22/07/ KG 23/07/ KG 24/07/ KG 25/07/ KG 26/07/ KG 27/07/ KG 28/07/ KG 29/07/ KG 30/07/ KG 31/07/ KG TOTAL BUNKERS CONSUMED: M/T Total Consumption: tons STEAM PRESS 15

16 Simulation in CHS: Total Consumption: CHS calc: Actual: tons tons Difference: 0.04% Heating practice followed was poor with two big heating up periods and constant use of the boiler for most part of the voyage 16

17 Alternative option using the automatic CHS Optimize function and the same loading and delivery temperatures: Total Consumption: CHS optimized: Actual: tons tons Fuel Saving: 37.2% (!) 17

18 Comments on worked example and savings: Actual practice was poor so there was a lot of room for improvement even without use of CHS hence the impressive savings figure. CHS was able to simulate actual measurements with very high accuracy. The schedule proposed by the CHS automatic optimizer algorithm includes a period of boiler off of 43 days and 9 days of heating up. During this procedure the cargo temperature drops to an average of 35.6 C, while cargo pour point is 9 C. If a higher temperature needs to be maintained during voyage CHS will automatically calculate the day when the boiler will need to be switched on and the %load that will need to be operated to maintain this temperature until the heating up to delivery temperature will need to start. Gains by applying optimization are higher on long voyages (>30 days) while minimal to nil at short voyages 18

19 Additional features and versions Capability to model non-heated tanks and simulate the effect of adjacent heated tanks Capability to include non-oil cargoes (e.g. veg-oils and chemicals) Capability to simulate temperature rise of chemicals carried in low temperature and determine the need to apply cooling in transit (e.g. propylene oxide cooling) Capability to simulate vessels with steam deck heaters and deep well pumps (e.g. FRAMO system) Capability to simulate thermal oil systems 19

20 Thank you for your attention!

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